• DocumentCode
    1551546
  • Title

    Blind equalization and channel estimation with partial response input signals

  • Author

    Tugnait, Jitendra K. ; Gummadavelli, Uma

  • Author_Institution
    Dept. of Electr. Eng., Auburn Univ., AL, USA
  • Volume
    45
  • Issue
    9
  • fYear
    1997
  • fDate
    9/1/1997 12:00:00 AM
  • Firstpage
    1025
  • Lastpage
    1031
  • Abstract
    The problem of blind equalization and channel estimation for partial-response signals (PRS) is considered. Three approaches are investigated; two of them exploit the prior knowledge of the PR code, and the third approach does not. We propose a constrained optimization approach involving a quadratic cumulant matching criterion where the coding structure of the transmitted signal is assumed to be a priori known. The other two approaches exploit the Godard blind equalizer. Computer simulation results using 16-QAM signals, and duobinary and modified duobinary PR codes, show that the constrained optimization approach yields the best performance as measured via the probability of symbol detection error
  • Keywords
    channel coding; digital communication; digital filters; equalisers; error statistics; estimation theory; higher order statistics; optimisation; partial response channels; quadrature amplitude modulation; 16-QAM signals; Godard blind equalizer; PR code; blind equalization; channel estimation; coding structure; constrained optimization approach; duobinary PR codes; input signals; modified duobinary PR codes; partial-response signals; performance; quadratic cumulant matching criterion; symbol detection error; transmitted signal; Adaptive signal processing; Bandwidth; Blind equalizers; Channel estimation; Constraint optimization; Data communication; Digital communication; Filters; Intersymbol interference; Limiting;
  • fLanguage
    English
  • Journal_Title
    Communications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0090-6778
  • Type

    jour

  • DOI
    10.1109/26.623064
  • Filename
    623064